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Glacier Mass Balance

2017· other· en· W4252485736 on OpenAlexaff
J. Graham Cogley

Bibliographic record

VenueInternational Encyclopedia of Geography · 2017
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsTrent University
Fundersnot available
KeywordsGlacierGeodetic datumGlacier mass balanceElevation (ballistics)SnowGeologyPhysical geographyClimate changeGeodesyEnvironmental scienceAtmospheric sciencesClimatologyGeomorphologyGeographyOceanographyPhysics

Abstract

fetched live from OpenAlex

The mass balance of a glacier is the change in its mass, over a stated span of time, due to accumulation (mass gain, mainly by snowfall) and ablation (mass loss, mainly by melting and calving). It is measured in situ by the so‐called glaciological method, or by geodetic methods relying on terrestrial, airborne, satellite surveys of elevation change, or gravimetrically by monitoring changes in the gravity field. Geodetic measurements require either modeling or in situ measurement of density in order to convert elevation change to mass change. In the gravimetric method the mass change is measured directly but with coarse spatial resolution. Nearly all glaciers have been losing mass since the culmination of the Little Ice Age and all projections by glacier–climate modeling agree that the losses will continue throughout the twenty‐first century.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.060
Threshold uncertainty score0.200

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0600.025

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.223
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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